Correlation

Correlation is the degree to which two sets of data are related and may
be mathematically calculated with the correlation coefficient (aka.
coefficient of correlation).

The simplest way of visualizing the
correlation is with a Scatter Diagram, where perfect correlation is a
straight line and no correlation is a random cloud of points. No
correlation is a positive result: it tells you clearly that the two sets
of data are not related. The must frustrating picture is when there is a
weak correlation which only says that there might be a weak or distant
relationship.

Low correlation

Positive correlation occurs when
increasing one set of data leads to a corresponding increase in the second
set of data. Negative correlation is when an increase in the first set
leads to a predictable decrease in the second set.

Negative Correlation

It is a trap to assume that
because correlation is found that there is a causal relationship. For
example, the sales of ice-cream correlate (i.e. go up and down with)
people drowning. One does not cause the other. In this case, they both
have a common cause: sunny weather.

At best, correlation can indicate a
potential relationship, which may be confirmed by other
methods.